activity
20242026
most citedEfficient Quantum Circuits for Machine Learning Activation Functions including Constant T-depth ReLU

3 citations · 5 across the 12 of their papers we have counts for

collaborators

12 papers

quant-ph2026

Quantum Arithmetic Circuits in Public-Key Cryptography

Siyi Wang, Kyungbae Jang, Hyunji Kim +4

Quantum computing has advanced rapidly in recent decades, driven by developments across the technology stack, including quantum error-correcting codes and efficient quantum algorit…

cs.CR2025

Efficient and Encrypted Inference using Binarized Neural Networks within In-Memory Computing Architectures

Gokulnath Rajendran, Suman Deb, Anupam Chattopadhyay

Binarized Neural Networks (BNNs) are a class of deep neural networks designed to utilize minimal computational resources, which drives their popularity across various applications.…

cs.CR2025

Securing the Internet of Medical Things (IoMT): Real-World Attack Taxonomy and Practical Security Measures

Suman Deb, Emil Lupu, Emm Mic Drakakis +4

The Internet of Medical Things (IoMT) has the potential to radically improve healthcare by enabling real-time monitoring, remote diagnostics, and AI-driven decision making. However…

quant-ph2025

SWAP Attack: Stealthy Side-Channel Attack on Multi-Tenant Quantum Cloud System

Wei Jie Bryan Lee, Siyi Wang, Suman Dutta +2

The rapid advancement of quantum computing has spurred widespread adoption, with cloud-based quantum devices gaining traction in academia and industry. This shift raises critical c…

quant-ph2025

On Exact Space-Depth Trade-Offs in Multi-Controlled Toffoli Decomposition

Suman Dutta, Siyi Wang, Anubhab Baksi +2

In this paper, we consider the optimized implementation of Multi Controlled Toffoli (MCT) using the Clifford T gate sets. While there are several recent works in this direction…

cs.LG2024

Federated Learning Optimization: A Comparative Study of Data and Model Exchange Strategies in Dynamic Networks

Alka Luqman, Yeow Wei Liang Brandon, Anupam Chattopadhyay

The promise and proliferation of large-scale dynamic federated learning gives rise to a prominent open question - is it prudent to share data or model across nodes, if efficiency o…